Senior System Software Engineer – Embedded AI Inference

Requirements

• 8+ years of professional software engineering experience, ideally in high-performance safety-critical software, automotive, robotics, or real-time systems.
• Master's or PhD degree in Computer Science or Machine Learning.
• Strong modern C++ (C++14/17 or later) skills.
• Solid Python skills for tooling, training scripts, and integrating with C++ components.
• Hands-on experience building agentic AI frameworks and with LLM / VLM inference.
• Experience developing on Linux with build systems, debugging, profiling, and git-based workflows.
• Familiarity with GPU programming and optimization, ideally experience with TensorRT.

Nice to Haves

• Experience with agentic AI frameworks and agents based on edge-friendly models.
• Direct experience with the NVIDIA DRIVE AGX platform.
• Knowledge of AI model optimization and deployment, including quantization techniques.
• Familiarity with high-performance LLM inference frameworks like TensorRT-LLM or ONNX Runtime.
• Understanding of software quality practices for safety-critical systems and open-source contributions in AI, robotics, or GPU computing.

What you'll be doing

• Design, implement, and maintain C++ agentic AI and AI inference solutions for embedded production platforms.
• Integrate PyTorch Deep Learning models into C++ pipelines and deploy for real-time inference on NVIDIA GPUs.
• Build and extend testable, modular libraries and components for in-car AI experiences.
• Profile, debug, and optimize C++ and CUDA code to meet latency and throughput targets.
• Collaborate with ML researchers, systems engineers, and automotive partners to bring prototype algorithms to production.

Perks and Benefits

• Work on challenging, real-world in-car AI inference problems.
• Collaborate with a talented, multidisciplinary team of researchers, engineers, and automotive experts.
• Solve hard technical problems at the intersection of deep learning, real-time systems, and production software engineering.